Chemically Selective Transport in a Cross-Linked H_II Phase Lyotropic Liquid Crystal Membrane

Abstract

The uniform size and complex chemical topology of the pores formed by self-assembled amphiphilic molecules such as liquid crystals make them promising candidates for selective separations. In this work, we observe the transport of water, sodium ions, and 20 small polar solutes within the pores of a lyotropic liquid crystal (LLC) membrane using atomistic molecular simulations. We find that the transport of a species is dependent not only on molecular size but also on chemical functionality. The membrane's inhomogeneous composition gives rise to radially dependent transport mechanisms with respect to the pore centers. We observe that all solutes perform intermittent hops between lengthy periods of entrapment. Three different trapping mechanisms are responsible for this behavior. First, solutes that drift out of the pore can become entangled among the dense monomer tails. Second, solutes can donate hydrogen bonds to the monomer head groups. Third, solutes can coordinate with sodium counterions. The degree to which a solute is affected by each mechanism is dependent on the chemical functionality of the solute. Using the insights developed in this study, we can begin to think about how to redesign existing LLC membranes to perform solute-specific separations.

Molecular insights on confined water in the nanochannels of self-assembled ionic liquid crystal

“…The addition of water molecules further enlarges the water pathway up to 1.1 nm. This trend of water pathway size corresponds with the computational result in the columnar structure of a lyotropic ILC by Shirts and co-worker ( 37 ). The same approach is difficult for the bicontinuous structure, since the spatial distribution of the 3D-interconnected nanochannel is different from the isolated one of unidirectional nanochannels formed in the columnar structure.…”

“…To investigate the nature of confined water inside the ionic nanochannel network, we simulated the self-assembled bicontinuous and columnar structures of compound 1 with the advanced force field and discussed the structural, energetic, and transport properties of water and ionic molecules confined in the ionic nanochannels relevant to the ILC polymer suggested as a reverse osmotic membrane ( 11 , 13 ). In this study, we mainly use TIP3P model as a standard reference to compare quantitative perspectives of confined water in the CNT, Nafion, and ILC nanochannels shown in previous reports ( 26 , 27 , 30 , 37 ). Furthermore, we demonstrate the universality of qualitative properties of water molecules inside the ILC nanochannels using TIP4P/2005 model ( 56 ).…”

Statistical Inference of Transport Mechanisms and Long Time Scale Behavior from Time Series of Solute Trajectories in Nanostructured Membranes

“…Approximately one-third of the water molecules occupy the tail region with the rest near the pore center. 7 We modeled water molecules using the TIP3P water model. 45 We used the Antechamber module shipped with AmberTools18 to parametrize monomers and solutes using the Generalized Amber Force Field (GAFF).…”

“…However, for the system that has captured our interest, this goal is complicated by the non-Brownian hopping and trapping behavior induced by the membrane's diverse topology and inhomogeneous structure resulting in subdiffusive behavior out to multiple microseconds of simulation. 6,7 A number of approaches have been explored to inexpensively extend the relatively short trajectories output by molecular simulations which exhibit complex diffusive behaviors onto much longer time scales. The trajectory extending kinetic Monte Carlo (TEKMC) approach divides a unit cell into a three-dimensional grid and quantifies the transition probabilities of particles that can move between each subdivision allowing one to generate stochastic trajectories that reach the diffusive regime.…”

“…11 Based on the chemical intuition gained from our previous qualitative MD studies of solute transport in an H II phase LLC membrane, we have contributed our own stochastic modeling approaches with goals similar to both TEKMC and DBP. 7,12 In previous studies, we identified three classes of trapping behavior which result in subdiffusion out to the microsecond time scale. In our first approach to stochastically model this behavior, we treated the system's dynamics as a sequence of anticorrelated hops between power law distributed periods of entrapment, a framework called subordinated fractional Brownian or Levy motion.…”